XLSR-WithLM-Malayalam

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the IMASC, Indic TTS Malayalam, OpenSLR Malayalam Train split datasets. It achieves the following results on the evaluation set:

  • Loss: 0.1395
  • Wer: 0.2952

Trigram Language Model Trained using KENLM Library on kavyamanohar/ml-sentences dataset

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.00024
  • train_batch_size: 1
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 4
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 800
  • num_epochs: 1
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.4912 0.1165 1000 0.5497 0.7011
0.5377 0.2330 2000 0.3292 0.5364
0.4343 0.3494 3000 0.2475 0.4424
0.3678 0.4659 4000 0.2145 0.4014
0.3345 0.5824 5000 0.1898 0.3774
0.3029 0.6989 6000 0.1718 0.3441
0.2685 0.8153 7000 0.1517 0.3135
0.2385 0.9318 8000 0.1395 0.2952

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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Evaluation results